Data Science I, Product Data Science

At Qualtrics, we create software the world’s best brands use to deliver exceptional frontline experiences, build high-performing teams, and design products people love. But we are more than a platform—we are the creators and stewards of the Experience Management category serving over 18K clients globally. Building a category takes grit, determination, and a disdain for convention—but most of all it requires close-knit, high-functioning teams with an unwavering dedication to serving our customers.

When you join one of our teams, you’ll be part of a nimble group that’s empowered to set aggressive goals and move fast to achieve them. Strategic risks are encouraged and complex problems are solved together, by passing the mic and iterating until the best solution comes to light. You won’t have to look to find growth opportunities—ready or not, they’ll find you. From retail to government to healthcare, we’re on a mission to bring humanity, connection, and empathy back to business. Join over 5,000 people across the globe who think that’s work worth doing.   Data Science I, Product Data Science

Why We Have This Role

Our product units need data scientists who can become trusted partners to Product and UX teams. They need people who understand the roadmap, ask the right questions before features get built, and design rigorous measurement to prove what's working. This isn't a role where you wait for requests and build dashboards. You'll be embedded with a product unit (CX, EX, or SR), becoming the go-to person for anything involving user behavior, experimentation, or product analytics.

How You’ll Find Success

• Be the first call for product decisions: Within 6 months, Product Managers and Designers will come to you before building features, not after. You'll build trust by delivering excellent work and being a proactive partner.
• Ship high-quality research quickly: You'll learn to move fast without sacrificing rigor. You'll know when an analysis needs causal inference and when a simple dashboard answers the question. You'll communicate findings clearly to non-technical stakeholders.
• Grow rapidly: You'll develop both technical depth (experimental design, causal inference, predictive modeling) and product sense (what questions matter, how to influence decisions). You'll get clear feedback and a path to senior levels.

How You’ll Grow

• Technical Depth: You'll develop expertise in product analytics and metrics, experimental design, causal inference, and predictive modeling.
• Product Sense: You'll learn what questions actually matter for product decisions and how to influence roadmaps with data.
• Career Path: You’ll have the opportunity to advance to more senior levels and grow your career with a leading SaaS company. You'll have regular feedback and clear development goals to get there.

Things You’ll Do

• Own instrumentation and measurement for your product unit: You’ll design event tracking strategies and user journeys. You’ll run golden path analysis to understand how key funnels in our product are behaving and how they can be improved. You’ll partner with engineering to ensure you have the data you need to be successful.
• Run experiments and quasi-experiments: You’ll design A/B tests and quasi-experimental studies to measure the impact of product changes and in-product messaging.
• Answer strategic questions that shape the roadmap: You’ll conduct everything from exploratory analysis to predictive analytics to answer strategic questions shaping the company roadmap.
• Cross-Functional Collaboration: You’ll partner with the leaders of User Research, Analytics and Analytics Engineering to ensure your work integrates with broader data and research strategies. You’ll communicate findings to product and executive leadership with clarity and impact.

What We’re Looking For On Your Resume

• Education & Experience: Master's or PhD in Statistics, Computer Science, Economics, Social Science, Hard Science or related quantitative field. 0-3 years of professional experience in data science, analytics, or research (internships count). Bachelor’s OK with additional relevant experience.
• Technical skills: Strong proficiency in Python or R for data analysis and modeling. Strong SQL skills. Knowledgeable in applied regression analysis, hypothesis testing, probability and predictive modeling. Experience with data visualization and communicating statistical results.
• Strong collaboration skills: Projects that demonstrate an ability to work in grou